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Duration 14 hours
Course Outline
Getting Started with the Mistral AI Ecosystem
- An overview of the Mistral model lineup (Medium 3, Le Chat Enterprise, Devstral)
- Understanding their role in the broader agentic AI landscape
- Identifying core features and competitive advantages
Foundations of Agent Design
- Defining the characteristics of an AI agent
- Establishing agent roles, memory structures, and toolsets
- Distinguishing between enterprise-focused and developer-centric agents
Practical Application of Mistral Medium 3
- Setting up and configuring the model
- Tuning and optimizing inference processes
- Managing multimodal and coding-centric workflows
Development with Devstral
- Designing code-centric agent architectures
- Leveraging Devstral for enhanced code comprehension
- Implementing best practices for engineering assistants
Integrating Le Chat Enterprise
- Implementing Le Chat for enterprise-scale agents
- Aligning with RBAC, SSO, and compliance frameworks
- Linking with enterprise applications and data repositories
Creating Complete Agent Workflows
- Synthesizing Mistral Medium 3, Devstral, and Le Chat capabilities
- Constructing multi-tool operations using connectors, APIs, and diverse data sources
- Applying grounding techniques and RAG patterns
Deployment Strategy and Governance
- Evaluating self-hosted solutions versus API-based deployment
- Implementing monitoring, logging, and observability standards
- Addressing cost efficiency, performance metrics, and compliance requirements
Recap and Future Directions
Requirements
- A solid foundation in Python programming
- Practical experience with machine learning processes
- Adequate knowledge of API interactions and model integration
Target Audience
- AI Engineers
- Solution Architects
- Applied Machine Learning Teams
- Product Developers
